Rethinking the Ranks of Visual Channels

• Published in: IEEE transactions on visualization and computer graphics Vol. 28; no. 1; pp. 707 - 717
• Main Authors: McColeman, Caitlyn M., Yang, Fumeng, Brady, Timothy F., Franconeri, Steven
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: and Plots; Bars; Channels; Charts; Computer memory; Correlation; Data visualization; DataType Agnostic; Diagrams; Displays; Error analysis; Human-Subjects Quantitative Studies; Measurement uncertainty; Memory management; Perception & Cognition; Ranking; Task analysis; Trends; Visualization

Data can be visually represented using visual channels like position, length or luminance. An existing ranking of these visual channels is based on how accurately participants could report the ratio between two depicted values. There is an assumption that this ranking should hold for different tasks...